Academic literature on the topic 'Combination model'

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Journal articles on the topic "Combination model"

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Burt, Tim, and J. R. O'Callaghan. "Novel Combination Model." Global Ecology and Biogeography Letters 7, no. 2 (1998): 152. http://dx.doi.org/10.2307/2997822.

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Zhang, X., and Y. Lei. "A linkage among whole-stand model, individual-tree model and diameter-distribution model." Journal of Forest Science 56, No. 12 (2010): 600–608. http://dx.doi.org/10.17221/102/2009-jfs.

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Stand growth and yield models include whole-stand models, individual-tree models and diameter-distribution models. In this study, the three models were linked by forecast combination and parameter recovery methods one after another. Individual-tree models combine with whole-stand models through forecast combination. Forecast combination method combines information from different models, disperses errors generated from different models, and then improves forecast accuracy. And then the forecast combination model was linked to diameter-distribution models via parameter recovery methods. During t
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N, Musliha, Liyana Faisal PP, and Raneem Ahammed Rashid K. "Neuropharmacological Assessment of Dual Herbal Combination Using Zebrafish Model." International Journal of Science and Research (IJSR) 11, no. 7 (2022): 1368–73. http://dx.doi.org/10.21275/sr22718201607.

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Lees, Kirdan, and Shaun P. Vahey. "Nowcasting and model combination." North American Journal of Economics and Finance 22, no. 1 (2011): 3–4. http://dx.doi.org/10.1016/j.najef.2011.01.003.

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de Moura, Leonardo, and Nikolaj Bjørner. "Model-based Theory Combination." Electronic Notes in Theoretical Computer Science 198, no. 2 (2008): 37–49. http://dx.doi.org/10.1016/j.entcs.2008.04.079.

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Lavanya, G., and D. Jasmine. "A Mathematical Model for Differentiated Thyroid Cancer with Combination Therapy." Indian Journal Of Science And Technology 17, no. 25 (2024): 2557–69. http://dx.doi.org/10.17485/ijst/v17i25.355.

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Objectives: Differentiated thyroid cancer (DTC) is usually treated with surgery and radioactive iodine therapy. However, in advanced stages, molecular changes can lead to a progressive loss of sensitivity to iodine, making the cancer resistant to radioactive iodine treatment (known as radioactive iodine-refractory, or RAIR). For cases of RAIR-DTC, alternative treatments such as tyrosine kinase inhibitors and immunotherapy are explored. To better understand the dynamics of these alternative treatments, a new mathematical model has been developed. In this model, Sorafenib represents the tyrosine
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Ting, Kai Ming, Boon Toh Low, and Ian H. Witten. "Learning from Batched Data: Model Combination Versus Data Combination." Knowledge and Information Systems 1, no. 1 (1999): 83–106. http://dx.doi.org/10.1007/bf03325092.

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Franses, Philip Hans. "Model selection for forecast combination." Applied Economics 43, no. 14 (2011): 1721–27. http://dx.doi.org/10.1080/00036840902762753.

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INOUE, Hiroyuki, and Yoshiyuki MURAMOTO. "Color Combination System Using Emotion Color Combination Model and Image Emotion Model and its Application to Uniform Color Combination." Transactions of Japan Society of Kansei Engineering 11, no. 2 (2012): 273–80. http://dx.doi.org/10.5057/jjske.11.273.

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Zhao, Wei, Kris Sachsenmeier, Lanju Zhang, Erin Sult, Robert E. Hollingsworth, and Harry Yang. "A New Bliss Independence Model to Analyze Drug Combination Data." Journal of Biomolecular Screening 19, no. 5 (2014): 817–21. http://dx.doi.org/10.1177/1087057114521867.

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The Bliss independence model is widely used to analyze drug combination data when screening for candidate drug combinations. The method compares the observed combination response ( YO) with the predicted combination response ( YP), which was obtained based on the assumption that there is no effect from drug-drug interactions. Typically, the combination effect is declared synergistic if YO is greater than YP. However, this method lacks statistical rigor because it does not take into account the variability of the response measures and can frequently cause false-positive claims. In this article,
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Dissertations / Theses on the topic "Combination model"

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Xu, Mingyang 1974. "Model combination by decomposition and aggregation." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/33641.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 2004.<br>Includes bibliographical references (p. 265-282).<br>This thesis focuses on a general problem in statistical modeling, namely model combination. It proposes a novel feature-based model combination method to improve model accuracy and reduce model uncertainty. In this method, a set of candidate models are first decomposed into a group of components or features and then components are selected and aggregated into a composite model based on data. However, in implementing this new method, some central ch
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Patterson, Merryl Joy. "Testing the weighted salience model of conceptual combination." Diss., Texas A&M University, 2003. http://hdl.handle.net/1969.1/270.

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In two experiments the Weighted Salience Model (WSM) of conceptual combination was examined. Several of the hypotheses set forth in the WSM were evaluated, including the importance of salience of constituent features, differential interpretation strategies based on similarity, an initial reliance on the modifier as opposed to the head, and a context effect of salience reorganization. Results confirmed that the hierarchy of output dominance within constituent features was important in determining features in final combinations. Additionally, similar pairs were defined with property interpreta
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Cook, G. D. "Data selection and model combination in connectionist speech recognition." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.597919.

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The hybrid connectionist-hidden Markov model (HMM) approach to large vocabulary continuous speech recognition has been shown to be competitive with HMM based systems. However, the recent availability of extremely large amounts of acoustic training data has highlighted a problem with the connectionist acoustic modelling paradigm. The effective use of such large amounts of data is difficult due to the computational requirements of training large connectionist models. This dissertation details research aimed at increasing the performance of connectionist acoustic models through the effective use
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Lipanova, Iuliia <1993&gt. "A model-combination approach to pricing for weather derivatives." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/8814.

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The main object of this study is to find a model that can explain and predict the behavior of weather time series. Different models of GARCH-type are fitted on the series of the average temperature. Autoregressive, seasonal and trend components are included in mean and variance equations. The seasonal components are constructed as a combination of simple harmonic functions, the frequencies of which are found with Fast Fourier Transform. Forecast combination approach is applied to define the best model and thus this model is used as an underlying to price weather derivatives. Numerical examples
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Makhtar, Mokhairi. "Contributions to Ensembles of Models for Predictive Toxicology Applications. On the Representation, Comparison and Combination of Models in Ensembles." Thesis, University of Bradford, 2012. http://hdl.handle.net/10454/5478.

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The increasing variety of data mining tools offers a large palette of types and representation formats for predictive models. Managing the models then becomes a big challenge, as well as reusing the models and keeping the consistency of model and data repositories. Sustainable access and quality assessment of these models become limited to researchers. The approach for the Data and Model Governance (DMG) makes easier to process and support complex solutions. In this thesis, contributions are proposed towards ensembles of models with a focus on model representation, comparison and usage. Predic
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Eastwood, Mark. "Building well-performing classifier ensembles : model and decision level combination." Thesis, Bournemouth University, 2010. http://eprints.bournemouth.ac.uk/18389/.

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There is a continuing drive for better, more robust generalisation performance from classification systems, and prediction systems in general. Ensemble methods, or the combining of multiple classifiers, have become an accepted and successful tool for doing this, though the reasons for success are not always entirely understood. In this thesis, we review the multiple classifier literature and consider the properties an ensemble of classifiers - or collection of subsets - should have in order to be combined successfully. We find that the framework of Stochastic Discrimination provides a well-def
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Harland, Zac. "Forecasting financial markets using linear, nonlinear & model combination methods." Thesis, City University London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.544436.

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Mei, Zhenyu, and Ye Tian. "Optimized combination model and algorithm of parking guidance information configuration." SpringerOpen, 2011. http://hdl.handle.net/10150/610136.

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Operators of parking guidance and information (PGI) systems often have difficulty in providing the best car park availability information to drivers in periods of high demand. A new PGI configuration model based on the optimized combination method was proposed by analyzing of parking choice behavior. This article first describes a parking choice behavioral model incorporating drivers perceptions of waiting times at car parks based on PGI signs. This model was used to predict the influence of PGI signs on the overall performance of the traffic system. Then relationships were developed for estim
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Zucchelli, D. "Combination Methods for Software Verification." Doctoral thesis, Università degli Studi di Milano, 2008. http://hdl.handle.net/2434/45877.

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The thesis is devoted to the development of formal methods for software verification. Indeed, two are among the most widespread techniques that allow to rigorously specify the possible executions of a system and check whether it contains bugs. On the one hand, the correctness of a program can be guaranteed by showing the unsatisfiability of a formula modulo a theory which usually axiomatizes the involved datatypes; on the other hand, the model checking techniques are used to certify that every possible run of the system satisfies the desired properties. The contributions of the thesis are the
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Brejova, Bronislava. "Evidence Combination in Hidden Markov Models for Gene Prediction." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/1036.

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This thesis introduces new techniques for finding genes in genomic sequences. Genes are regions of a genome encoding proteins of an organism. Identification of genes in a genome is an important step in the annotation process after a new genome is sequenced. The prediction accuracy of gene finding can be greatly improved by using experimental evidence. This evidence includes homologies between the genome and databases of known proteins, or evolutionary conservation of genomic sequence in different species. <br /><br /> We propose a flexible framework to incorporate several different
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Books on the topic "Combination model"

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Costello, F. A model-based theory of concept combination. Trinity College Dublin, 1992.

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Moriarty, Mark M. Marketing forecasting with the combination of forecasts: An implementation model. Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1988.

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D'Amico, Stefania. Density selection and combination under model ambiguity: An application to stock returns. Federal Reserve Board, 2005.

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Howell, Syd. A state space model for comparing types of separate and combination forecasts. Manchester Business School, 1995.

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Howell, Syd. A state space model for comparing types of separate and combination forecasts. Manchester Business School, 1995.

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Perez, Marc. A Model for Optimizing the Combination of Solar Electricity Generation, Supply Curtailment, Transmission and Storage. [publisher not identified], 2014.

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Varma, Pryamvada Yasomatee. Effect of combination Ikl and Ikr blockade on defibrillation and cardiac refractoriness in the isolated langendorff rabbit heart model. National Library of Canada, 2000.

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Studiedienst van de Vlaamse Regering, ed. Towards a democratic division of labour in Europe?: The combination model as a new integrated approach to professional and family life. Policy Press, 2009.

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P, Bezler, U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Engineering., and Brookhaven National Laboratory, eds. Alternate modal combination methods in response spectrum analysis. Division of Engineering, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1990.

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R, Berger Martin, ed. Combination effects in chemical carcinogenesis. VCH, 1988.

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Book chapters on the topic "Combination model"

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Yuan, Ying, Ruitao Lin, and J. Jack Lee. "Drug-Combination Trials." In Model-Assisted Bayesian Designs for Dose Finding and Optimization. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9780429052781-4.

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Dodge, Yadolah, and Jana Jurečková. "Adaptive Combination of Tests." In Goodness-of-Fit Tests and Model Validity. Birkhäuser Boston, 2002. http://dx.doi.org/10.1007/978-1-4612-0103-8_31.

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Liu, Yong, Austin Ford Ramsey, and Ziqin Zhou. "Model and Forecast Combination for Predictive Yield Distributions in Crop Insurance." In Springer Actuarial. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-80574-5_8.

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Abstract Multiple-peril crop insurance policies require statistical modeling of probability distributions of crop yields. Unfortunately, no single parametric distribution is likely to capture the true data generating process. Likewise, non-parametric approaches converge to the true distribution at a slow rate; yield histories are often of modest size. Recognizing these shortcomings, model and forecast combination are now being applied in crop insurance settings. Model and forecast combination avoid the dangers inherent in selecting a single model for the predictive yield distribution. The comp
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Fathy, N., and Daniel E. Furst. "Combination therapy for autoimmune diseases: the rheumatoid arthritis model." In Combination Treatment in Autoimmune Diseases. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04759-0_2.

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Singhi, Surendra K., and Huan Liu. "Error-Sensitive Grading for Model Combination." In Machine Learning: ECML 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11564096_74.

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Hemri, Stephan. "Multi-model Combination and Seamless Prediction." In Handbook of Hydrometeorological Ensemble Forecasting. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-40457-3_19-1.

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Hemri, Stephan. "Multi-model Combination and Seamless Prediction." In Handbook of Hydrometeorological Ensemble Forecasting. Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-642-39925-1_19.

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Aggarwal, Charu C., and Saket Sathe. "Model Combination Methods for Outlier Ensembles." In Outlier Ensembles. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54765-7_5.

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Chatterjee, Soma, and Kamal Sarkar. "Bengali Document Retrieval Using Model Combination." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2680-0_9.

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Englund, Cristofer, and Antanas Verikas. "A SOM Based Model Combination Strategy." In Advances in Neural Networks — ISNN 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11427391_73.

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Conference papers on the topic "Combination model"

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Zhao, Shiyi, Yidan Zhang, Nannan Xia, Kai Zhang, Jipeng Kuai, and Ye Zhang. "Research on Electricity Price Prediction Based on Combination Model." In 2024 3rd International Conference on Energy and Electrical Power Systems (ICEEPS). IEEE, 2024. http://dx.doi.org/10.1109/iceeps62542.2024.10693046.

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Xia, Huayi. "Power Load Forecasting Based on CNN-LSTM Combination Model." In 2024 IEEE 2nd International Conference on Image Processing and Computer Applications (ICIPCA). IEEE, 2024. http://dx.doi.org/10.1109/icipca61593.2024.10709194.

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Ali, Hyacinth, Gunter Mussbacher, and Jorg Kienzle. "Towards Modular Combination and Reuse of Languages with Perspectives." In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2019. http://dx.doi.org/10.1109/models-c.2019.00060.

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Philippe, Jolan, Héléne Coullon, Massimo Tisi, and Gerson Sunyé. "Towards transparent combination of model management execution strategies for low-code development platforms." In MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems. ACM, 2020. http://dx.doi.org/10.1145/3417990.3420206.

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Zhao, Hui, Ludovic Apvrille, and Frédéric Mallet. "Meta-models Combination for Reusing Verification Techniques." In 7th International Conference on Model-Driven Engineering and Software Development. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007261000370048.

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Zhao, Hui, Ludovic Apvrille, and Frédéric Mallet. "Meta-models Combination for Reusing Verification Techniques." In 7th International Conference on Model-Driven Engineering and Software Development. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007261000390050.

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Monteith, Kristine, James L. Carroll, Kevin Seppi, and Tony Martinez. "Turning Bayesian model averaging into Bayesian model combination." In 2011 International Joint Conference on Neural Networks (IJCNN 2011 - San Jose). IEEE, 2011. http://dx.doi.org/10.1109/ijcnn.2011.6033566.

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Li, Meijuan, Guohong Chen, Zhibing Lin, and Binqing Cai. "Combination Forecasting Model Based on Drift." In 2009 International Joint Conference on Computational Sciences and Optimization, CSO. IEEE, 2009. http://dx.doi.org/10.1109/cso.2009.26.

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Zheng, Zhiqiang, Balaji Padmanabhan, and Haoqiang Zheng. "A DEA approach for model combination." In the 2004 ACM SIGKDD international conference. ACM Press, 2004. http://dx.doi.org/10.1145/1014052.1014152.

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Zhu, Xiaowen, and Yinglin Wang. "A Relation Combination Model for Knowledge Maps." In 2009 International Conference on Information Engineering and Computer Science. IEEE, 2009. http://dx.doi.org/10.1109/iciecs.2009.5364816.

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Reports on the topic "Combination model"

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Bajari, Patrick, Denis Nekipelov, Stephen Ryan, and Miaoyu Yang. Demand Estimation with Machine Learning and Model Combination. National Bureau of Economic Research, 2015. http://dx.doi.org/10.3386/w20955.

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Rowson, Peter C. A COMBINATION OF PRELIMINARY ELECTROWEAK MEASUREMENTS AND CONSTRAINTS ONTHE STANDARD MODEL. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/801809.

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Abbaneo, J. A Combination of Preliminary Electroweak Measurements and Constraints on the Standard Model. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/826675.

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Su, Dong. A Combination of Preliminary Electroweak Measurements and Constraints on the Standard Model. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/813338.

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De Groot, Nicolo. A Combination of Preliminary Electroweak Measurements and Constraints on the Standard Model. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/815298.

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Abbaneo, D. A Combination of Preliminary Electroweak Measurements And Constraints on the Standard Model (2004). Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/839900.

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Previtali, Marco, Matteo Ciantia, Saverio Spadea, Riccardo Castellanza, and Giovanni Crosta. Development of a macro-element model for rockfall steel wires using. University of Dundee, 2021. http://dx.doi.org/10.20933/100001232.

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This paper aims to present a few aspects of the development of a plastic-hardening macro-element model for steel wires in flexible protection systems. First, the material behaviour is obtained using uniaxial tensile tests. Successively, the evolution of the elastic and plastic domain is obtained using a combination of physical tests, analytical models, and numerical simulations. Finally, the results obtained with the macro-element model are compared to those obtained using other approaches found in literature.
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Hajdini, Ina. Mis-specified Forecasts and Myopia in an Estimated New Keynesian Model. Federal Reserve Bank of Cleveland, 2023. http://dx.doi.org/10.26509/frbc-wp-202203r.

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The paper considers a New Keynesian framework in which agents form expectations based on a combination of autoregressive mis-specified forecasts and myopia. The proposed expectations formation process is shown to be consistent with all three empirical facts on consensus inflation forecasts. However, while mis-specified forecasts can be both sufficient and necessary to match all three facts, myopia alone is neither. The paper then derives the general equilibrium solution consistent with the proposed expectations formation process and estimates the model with likelihood-based Bayesian methods, y
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Sutherland, Mary. Hydrogeologic investigation of the Belgrade-Manhattan area, Gallatin County, Montana: Superposition groundwater modeling report. Montana Bureau of Mines and Geology, 2023. http://dx.doi.org/10.59691/fcfu8406.

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An interpretive report of the findings from the Belgrade-Manhattan groundwater model. The report focuses on the results of a superposition model looking at water resources in the northern half of the Gallatin Valley. Data from the study are included to a lesser extent as the report is a combination model and interpretive report.
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Francis, Andrew, Chas Jandu, and Mike Taylor. PR-408-124500-R01 Mechanical Damage Instantaneous Failure Model Numerical Simulation of Physical Tests. Pipeline Research Council International, Inc. (PRCI), 2013. http://dx.doi.org/10.55274/r0010819.

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The overall objective was to develop two models for determining the effect of mechanical damage on the structural integrity of buried pipelines. The models that are to be developed are the instantaneous failure model (MD4-3) and the delayed failure model (MD4-4). The subject of this report is part of the work that has been undertaken in support of the development of the instantaneous failure model which is being undertaken within the remit of MD4-3. The overall objective of MD4-3 to produce a closed form expression that will be used as: (i) A Limit State Function in structural reliability and
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